Virtual, US
5 hours ago
Bilingual Machine Learning Data Associate - Dutch (Remote), Customer Engagement Technology
The Customer Engagement Technologies (CET) organization powers Customer Service (CS) by developing elegant customer- and Customer Service Associate (CSA)-facing products globally. These products offer effortless self-service and automated solutions to our customers. When customers prefer to interact with a human, we enable CSAs to effectively and elegantly solve customers' issues using our associate-facing products powered by human-centered design. One of these solutions is a new translation system deploying neural machine translation technology (through AWS Translate models) that supports high-quality, real-time translations for up to 39 languages. By applying automated translations to text-based customer service channels (e-mail, chat, Message Us, and CS Chatbot), the product's vision is to remove language as a barrier and enable flexibility in the CS labor force. Ultimately, Amazon will be capable of supporting customers anywhere around the world, regardless of the language the CSA speaks.

Our team is looking for a talented Machine Learning Data Associate (MLDA) - Specialist in Dutch to drive Dutch-to-English and English-to-Dutch machine translation improvements in partnership with the Machine Learning team. Specifically, you will:
- Audit cross-language interactions on text-based channels
- Review and assess the quality of machine translations in each direction
- Identify the highest priority machine translation improvement opportunities to enhance the customer experience

You will work with Program and Product Managers to determine opportunities for optimizing quality auditing and machine translation improvement processes, augmenting the customer experience through product testing, and executing the machine learning roadmap for the product. You will be part of a Global Product Management team whose innovations and strategies will influence what we build and how we surface information to solve customers' issues globally.

The successful candidate is a native Dutch speaker who also speaks English fluently, is extremely detail-oriented, and an effective communicator, and has demonstrated the ability to earn stakeholders' trust across cross-functional teams. The ideal candidate is data-driven and has a strong eye for opportunities. You should be customer-obsessed and comfortable analyzing thousands of interactions. You are willing to experiment, fail fast, learn, and iterate to improve. Furthermore, you understand and account for the implications of your work on front-line operations.

Key job responsibilities
- Proficiency in testing and content proofreading in Dutch, with the ability to document outcomes in English for stakeholders
- Utilization of Dutch language skills to support internal and external customers and their related products
- Competence in navigating various internal tools to understand the customer journey
- Strong attention to detail and commitment to quality
- Adaptability to work in a dynamic environment and willingness to adjust priorities on short notice
- Fluency in Dutch and English (required)

A day in the life
Key daily activities include, but are not limited to:
- Localization and Translation
- Testing of various workstreams
- Contract Reading in native language while documenting findings in English
- Stakeholder management
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.

The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan.

About the team
Omni MLDA is a division of Customer Engagement Technologies (CET), partnering with key stakeholders to:
- Automate customer service processes
- Enhance the end-to-end customer experience
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